Master Thesis, Internship

Internship or Master Thesis on NVMe Computational Storage: Revising the Computational Offloading

Ref. 2024_021

Project description

Since NVMe 2.1 (Aug 2024), the Computational Command Set (CCS) specification has been ratified in the NVMe 2.1 specification. With that now there is a push for a standardized approach towards program offloading in NVMe devices. However with its new API and the nature of offload type - there is uncertainty regarding what programs, workflows can benefit from such offloading capability. We are interested in the following research questions:

  1. Are there specific domains of applications that have particular affinity towards computational offloading as offered by the NVMe CCS?
  2. In recent years there has been a renewed interest in building out-of-core graph processing systems. Can out-of-core graph processing systems benefit from the NVMe CCS specification?
  3. Design and implement a simulator and performance reasoning model for graph offloading: The goal is to identify various opportunities on how we can develop SSDs, storage stacks, and graph processing frameworks to deliver end-to-end performance gains. Hence, we would like to answer “what-if” questions like: What if SSD reads were 10x faster? What is the impact of graph operator offloading to SSD?

Qualifications:

  • Enrolled or in possession of a Master's degree in computer science with a keen interest in data storage research, cloud computing and performance engineering.
  • Excellent coding skills: Familiarity with Linux environments and software development tools (git/GitHub, IDEs, gcc, gdb, QEMU, virtual machine and containers etc.).
  • High creativity and outstanding problem-solving ability.

Preferred Qualifications:

  • Experience with systems programming and internals (kernel, memory management, hardware, CPU)
  • Experience with data storage and NVMe storage internals and specification
  • Experience in machine learning or cloud
  • Experience with performance engineering tools (perf, fio, ebpf)
  • Excellent oral and written English with good presentation skills.
  • Strong interpersonal skills and excellent written and verbal communication.

Diversity

IBM is committed to diversity at the workplace. With us you will find an open, multicultural environment. Excellent flexible working arrangements enable all genders to strike the desired balance between their professional development and their personal lives.

How to apply

Please submit your application through the link below. This position is available starting immediately or at a later date.